Harnessing Large Language Models for Disaster Management: A Survey

• URL: http://arxiv.org/abs/2501.06932v1
• Date: Sun, 12 Jan 2025 21:00:50 GMT
• Title: Harnessing Large Language Models for Disaster Management: A Survey
• Authors: Zhenyu Lei, Yushun Dong, Weiyu Li, Rong Ding, Qi Wang, Jundong Li,
• Abstract summary: Large language models (LLMs) have revolutionized scientific research with their exceptional capabilities and transformed various fields. This study aims to guide the professional community in developing advanced LLMs for disaster management to enhance the resilience against natural disasters.
• Score: 57.00123968209682
• License:
• Abstract: Large language models (LLMs) have revolutionized scientific research with their exceptional capabilities and transformed various fields. Among their practical applications, LLMs have been playing a crucial role in mitigating threats to human life, infrastructure, and the environment. Despite growing research in disaster LLMs, there remains a lack of systematic review and in-depth analysis of LLMs for natural disaster management. To address the gap, this paper presents a comprehensive survey of existing LLMs in natural disaster management, along with a taxonomy that categorizes existing works based on disaster phases and application scenarios. By collecting public datasets and identifying key challenges and opportunities, this study aims to guide the professional community in developing advanced LLMs for disaster management to enhance the resilience against natural disasters.

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